With the advent of digital communication and social networking sites, more and more of our social interactions has become through these social networking sites. The technology is also available to provide a communication infrastructure enabling fast, efficient and reliable transport of this information from the providers of information.
The word of mouth distribution of information, i.e. passing information from person to person, constitutes another channel to assist users in identifying information of interest to them. A user who knows the information tells it to his friends, who then tell it to their friends and so on.
Several researchers have explored social networks for designing algorithms for spreading messages by finding influential users and communities. One popular practice employed by many brands is to broadcast the same message to multiple users. However, the broadcast method would not scale with increasing number of messages, as the users will start considering the broadcast messages as spam and ignore the messages.
One method is to select a certain number of people having the most friends. However, people selected by this method frequently are in the same social community and circle of friends and only cover a portion of the entire social network. Therefore, this method usually does not reach the maximum coverage. Another way of finding influencers is to try all combinations of a certain number of people that will maximize the spreading of the electronic message. However, this requires an inordinate amount of computation time, and therefore is not a feasible alternative. Therefore, there is a need for a method to control and measure flow of electronic message in the social network by identifying key influencer responsible for spreading the messages.